Rapid transit vehicles employing cam type propulsion control units present several problems for the automatic speed control of those transit vehicles. The discrete states or levels of tractive effort inherent in cam propulsion systems and the inability to command certain state to state transistions are somewhat incompatible with microprocessor based continuous type speed control systems such as described in U.S. Pat. No. 4,282,466 of T. C. Matty and entitled Transit Vehicle Motor Effort Control Apparatus and Method in relation to a chopper propulsion motor control system. Furthermore the cam state to state transition delay times and the increased equipment wear resulting from decreases in both positive and negative tractive effort present difficulties for the speed control apparatus and method.
It is desired for the Washington Metropolitan Area Transit Authority (WMATA) to provide an improved speed control apparatus and method responding to two primary control criteria, namely the vehicle speed has to be maintained within a predetermined speed band, such as a plus zero to minus four mile per hour speed band, relative to the commanded vehicle speed, and the number of adverse state changes has to be kept below six changes per minute. An adverse state change is defined as a decrease in either positive or negative tractive effort. Decreases in tractive effort are obtained in cam propulsion apparatus by opening resistor shorting switches. Since this action severely stresses these switches, the adverse change restriction is intended to reduce wear on the propulsion equipment and therefore extend equipment life. The previous automatic train speed control equipment controlling the cam propulsion units for the WMATA transit vehicles requests more than six adverse state changes per minute.
The previous WMATA train control apparatus includes twelve train lines over which the propulsion equipment and the ATC equipment communicate. There are ten specific propulsion train line patterns and five specific brake train line patterns in addition to a coast train line pattern which can be selected by the ATC equipment. These sixteen train line patterns, corresponding to sixteen states of the propulsion system operation, provide sixteen different levels of positive and negative tractive effort. WMATA, however, only uses fourteen of these states and only fourteen will be considered hereafter, since two propulsion states are not used. The adverse change limitation on train state transitions applies to changes in the train line pattern outputted by the ATC equipment.
The problem of speed maintaining within a four mile per hour band is not particularly difficult. A prior art proportional or proportional plus integral controller will successfully maintain speed with some modification to account for closed loop stability and certain unavailable state transitions while attempting to decrease tractive effort while in propulsion. This approach however results in more adverse state changes than desired.
A speed control approach simulating an ideal human operator is appropriate. An ideal human operator observes the train speed relative to the speed control band, and approximates the train acceleration in relation to forthcoming track conditions. He understands the undesirable effects of adverse state changes and therefore acts to minimize them. If he is speed maintaining low in the speed band and accelerating slightly he would take no action at that time. If on the other hand he were decelerating while low in the speed maintaining band he would transfer to a state providing more tractive effort. In addition he would not overreact, but would wait out the train delays to see the effect of the state transitions. Furthermore if a decrease in tractive or retarding effort were required he might transfer to a state sufficiently removed from the present state to assure that sufficient reduction occurs in an effort to reduce the number of adverse state transitions. A return to the coast state in this example would reverse the acceleration or deceleration under most conditions and result in the fewest adverse transitions. In this manner by monitoring speed, acceleration and the speed band while being aware of train delays, adverse transitions, and track conditions, an ideal human properly controls train performance. In addition there is a learning process that a human operator undergoes to improve his decision making ability with experience.